The project involves analyzing certain issues of customer churn faced by telecom companies. Models are required to be built so as to predict whether a customer will cancel their service in the future or not and then model comparison measures are made for taking interpretation and recommendations from the best model.

The project aims at predicting whether a patient is likely to get a stroke based on the input parameters like gender, age, BMI, average glucose level, various diseases like hypertension, heart disease, and smoking status. (Course: CSL2050 Pattern Recognition and Machine Learning)

Here we will be firstly analysing the how different threshold values effect the area under the Curve in a Receiver Operating charcteristic(ROC) curve. And at last we will show how to define a function in python to calculate the most optimal threshold value for the logistic Regression.

Virginia Environment Sensitivity Index (ESI) Maps GIS Data. GIS formats converted to .geojson/.topojson, .pdf converted to .png/.csv/.xlsx where applicable. more to come...

analysis

Calculation of sensitivity coefficients and visualization

To predict which customer is most likely to convert

Nonparametric comparison of convolutional neural networks and transformers to classify COVID-19

Predicting Heart Disease using Machine Learning

Repository for a Masters internship for the master Toxicology and Environmental health, The purpose of this internship is to develop a QIVIVE model for Cinnamaldehyde

DiaMetrics is a web-based educational resource for exploring important concepts regarding binary classification (and its evaluation), which is important in many different fields such as psychodiagnostics (e.g. in determining cut-off values for tests), machine learning or medical testing.

📦 Data and R code to explore sensitivity of subantarctic invertebrates to warming - Renault et al. (2022) [https://doi.org/10.1111/gcb.16338]

Evaluation of the performance of classification models can be facilitated through a combination of calculating certain types of performance metrics and generating model performance evaluation graphics. The purpose of this exercise is to calculate a suite of classification model performance metrics via Python code functions.

DiaMetrics_DE is the German version of Diametrics: a web-based educational resource for exploring important concepts regarding binary classification (and its evaluation), which is important in many different fields such as psychodiagnostics (e.g. in determining cut-off values for tests), machine learning or medical testing.

Taste threshold estimation using QUEST.

CRS: Composite Reference Standard in R

This python script used to model the MQ6 gas sensor and calculate the PPM